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Azure Monitor and Snowflake Integration

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This is not the recommended configuration for real-time query at scale. For query and compression optimization, high-speed ingest, and high availability, you may want to consider <a href="/integrations/azure_monitor-influxdb/">Azure Monitor and InfluxDB</a>.

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Infrastructure Monitoring with Telegraf

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Input and output integration overview

<p>Gather metrics from Azure resources using the Azure Monitor API.</p>

<p>Telegraf’s SQL plugin allows seamless metric storage in SQL databases. When configured for Snowflake, it employs a specialized DSN format and dynamic table creation to map metrics to the appropriate schema.</p>

Integration details

Azure Monitor

<p>The Azure Monitor Telegraf plugin is specifically designed for gathering metrics from various Azure resources using the Azure Monitor API. Users must provide specific credentials such as <code>client_id</code>, <code>client_secret</code>, <code>tenant_id</code>, and <code>subscription_id</code> to authenticate and gain access to their Azure resources. Additionally, the plugin supports functionality to collect metrics from both individual resources and resource groups or subscriptions, allowing for flexible and scalable metric collection tailored to user needs. This plugin is ideal for organizations leveraging Azure cloud infrastructure, providing crucial insights into resource performance and utilization over time, facilitating proactive management and optimization of cloud resources.</p>

Snowflake

<p>Telegraf’s SQL plugin is engineered to dynamically write metrics into an SQL database by creating tables and columns based on the incoming data. When configured for Snowflake, it employs the gosnowflake driver, which uses a DSN that encapsulates credentials, account details, and database configuration in a compact format. This setup allows for the automatic generation of tables where each metric is recorded with precise timestamps, thereby ensuring detailed historical tracking. Although the integration is considered experimental, it leverages Snowflake’s powerful data warehousing capabilities, making it suitable for scalable, cloud-based analytics and reporting solutions.</p>

Configuration

Azure Monitor

<pre><code class="language-toml"># Gather Azure resources metrics from Azure Monitor API [[inputs.azure_monitor]] # can be found under Overview-&gt;Essentials in the Azure portal for your application/service subscription_id = "&lt;<SUBSCRIPTION_ID>&gt;" # can be obtained by registering an application under Azure Active Directory client_id = "&lt;<CLIENT_ID>&gt;" # can be obtained by registering an application under Azure Active Directory. # If not specified Default Azure Credentials chain will be attempted: # - Environment credentials (AZURE_*) # - Workload Identity in Kubernetes cluster # - Managed Identity # - Azure CLI auth # - Developer Azure CLI auth client_secret = "&lt;<CLIENT_SECRET>&gt;" # can be found under Azure Active Directory-&gt;Properties tenant_id = "&lt;<TENANT_ID>&gt;" # Define the optional Azure cloud option e.g. AzureChina, AzureGovernment or AzurePublic. The default is AzurePublic. # cloud_option = "AzurePublic" # resource target #1 to collect metrics from [[inputs.azure_monitor.resource_target]] # can be found under Overview-&gt;Essentials-&gt;JSON View in the Azure portal for your application/service # must start with 'resourceGroups/...' ('/subscriptions/xxxxxxxx-xxxx-xxxx-xxx-xxxxxxxxxxxx' # must be removed from the beginning of Resource ID property value) resource_id = "&lt;<RESOURCE_ID>&gt;" # the metric names to collect # leave the array empty to use all metrics available to this resource metrics = [ "&lt;<METRIC>&gt;", "&lt;<METRIC>&gt;" ] # metrics aggregation type value to collect # can be 'Total', 'Count', 'Average', 'Minimum', 'Maximum' # leave the array empty to collect all aggregation types values for each metric aggregations = [ "&lt;<AGGREGATION>&gt;", "&lt;<AGGREGATION>&gt;" ] # resource target #2 to collect metrics from [[inputs.azure_monitor.resource_target]] resource_id = "&lt;<RESOURCE_ID>&gt;" metrics = [ "&lt;<METRIC>&gt;", "&lt;<METRIC>&gt;" ] aggregations = [ "&lt;<AGGREGATION>&gt;", "&lt;<AGGREGATION>&gt;" ] # resource group target #1 to collect metrics from resources under it with resource type [[inputs.azure_monitor.resource_group_target]] # the resource group name resource_group = "&lt;<RESOURCE_GROUP_NAME>&gt;" # defines the resources to collect metrics from [[inputs.azure_monitor.resource_group_target.resource]] # the resource type resource_type = "&lt;<RESOURCE_TYPE>&gt;" metrics = [ "&lt;<METRIC>&gt;", "&lt;<METRIC>&gt;" ] aggregations = [ "&lt;<AGGREGATION>&gt;", "&lt;<AGGREGATION>&gt;" ] # defines the resources to collect metrics from [[inputs.azure_monitor.resource_group_target.resource]] resource_type = "&lt;<RESOURCE_TYPE>&gt;" metrics = [ "&lt;<METRIC>&gt;", "&lt;<METRIC>&gt;" ] aggregations = [ "&lt;<AGGREGATION>&gt;", "&lt;<AGGREGATION>&gt;" ] # resource group target #2 to collect metrics from resources under it with resource type [[inputs.azure_monitor.resource_group_target]] resource_group = "&lt;<RESOURCE_GROUP_NAME>&gt;" [[inputs.azure_monitor.resource_group_target.resource]] resource_type = "&lt;<RESOURCE_TYPE>&gt;" metrics = [ "&lt;<METRIC>&gt;", "&lt;<METRIC>&gt;" ] aggregations = [ "&lt;<AGGREGATION>&gt;", "&lt;<AGGREGATION>&gt;" ] # subscription target #1 to collect metrics from resources under it with resource type [[inputs.azure_monitor.subscription_target]] resource_type = "&lt;<RESOURCE_TYPE>&gt;" metrics = [ "&lt;<METRIC>&gt;", "&lt;<METRIC>&gt;" ] aggregations = [ "&lt;<AGGREGATION>&gt;", "&lt;<AGGREGATION>&gt;" ] # subscription target #2 to collect metrics from resources under it with resource type [[inputs.azure_monitor.subscription_target]] resource_type = "&lt;<RESOURCE_TYPE>&gt;" metrics = [ "&lt;<METRIC>&gt;", "&lt;<METRIC>&gt;" ] aggregations = [ "&lt;<AGGREGATION>&gt;", "&lt;<AGGREGATION>&gt;" ] &lt;/code&gt;&lt;/pre&gt; </AGGREGATION></AGGREGATION></METRIC></METRIC></RESOURCE_TYPE></AGGREGATION></AGGREGATION></METRIC></METRIC></RESOURCE_TYPE></AGGREGATION></AGGREGATION></METRIC></METRIC></RESOURCE_TYPE></RESOURCE_GROUP_NAME></AGGREGATION></AGGREGATION></METRIC></METRIC></RESOURCE_TYPE></AGGREGATION></AGGREGATION></METRIC></METRIC></RESOURCE_TYPE></RESOURCE_GROUP_NAME></AGGREGATION></AGGREGATION></METRIC></METRIC></RESOURCE_ID></AGGREGATION></AGGREGATION></METRIC></METRIC></RESOURCE_ID></TENANT_ID></CLIENT_SECRET></CLIENT_ID></SUBSCRIPTION_ID></code></pre>

Snowflake

<pre><code class="language-toml">[[outputs.sql]] ## Database driver ## Valid options: mssql (Microsoft SQL Server), mysql (MySQL), pgx (Postgres), ## sqlite (SQLite3), snowflake (snowflake.com), clickhouse (ClickHouse) driver = "snowflake" ## Data source name ## For Snowflake, the DSN format typically includes the username, password, account identifier, and optional warehouse, database, and schema. ## Example DSN: "username:password@account/warehouse/db/schema" data_source_name = "username:password@account/warehouse/db/schema" ## Timestamp column name timestamp_column = "timestamp" ## Table creation template ## Available template variables: ## {TABLE} - table name as a quoted identifier ## {TABLELITERAL} - table name as a quoted string literal ## {COLUMNS} - column definitions (list of quoted identifiers and types) table_template = "CREATE TABLE {TABLE} ({COLUMNS})" ## Table existence check template ## Available template variables: ## {TABLE} - table name as a quoted identifier table_exists_template = "SELECT 1 FROM {TABLE} LIMIT 1" ## Initialization SQL (optional) init_sql = "" ## Maximum amount of time a connection may be idle. "0s" means connections are never closed due to idle time. connection_max_idle_time = "0s" ## Maximum amount of time a connection may be reused. "0s" means connections are never closed due to age. connection_max_lifetime = "0s" ## Maximum number of connections in the idle connection pool. 0 means unlimited. connection_max_idle = 2 ## Maximum number of open connections to the database. 0 means unlimited. connection_max_open = 0 ## Metric type to SQL type conversion ## Defaults to ANSI/ISO SQL types unless overridden. Adjust if needed for Snowflake compatibility. #[outputs.sql.convert] # integer = "INT" # real = "DOUBLE" # text = "TEXT" # timestamp = "TIMESTAMP" # defaultvalue = "TEXT" # unsigned = "UNSIGNED" # bool = "BOOL" </code></pre>

Input and output integration examples

Azure Monitor

<ol> <li> <p><strong>Dynamic Resource Monitoring</strong>: Use the Azure Monitor plugin to dynamically gather metrics from Azure resources based on specific criteria like tags or resource types. Organizations can automate the process of loading and unloading resource metrics, enabling better performance tracking and optimization based on resource utilization patterns.</p> </li> <li> <p><strong>Multi-Cloud Monitoring Integration</strong>: Integrate metrics collected from Azure Monitor with other cloud providers using a centralized monitoring solution. This allows organizations to view and analyze performance data across multiple cloud deployments, providing a holistic overview of resource performance and costs, and streamlining operations.</p> </li> <li> <p><strong>Anomaly Detection and Alerting</strong>: Leverage the metrics gathered via the Azure Monitor plugin in conjunction with machine learning algorithms to detect anomalies in resource utilization. By establishing baseline performance metrics and automatically alerting on deviations, organizations can mitigate risks and address performance issues before they escalate.</p> </li> <li> <p><strong>Historical Performance Analysis</strong>: Use the collected Azure metrics to conduct historical analysis by feeding the data into a data warehousing solution. This enables organizations to track trends over time, allowing for detailed reporting and decision-making based on historical performance data.</p> </li> </ol>

Snowflake

<ol> <li> <p><strong>Cloud-Based Data Lake Integration</strong>: Utilize the plugin to stream real-time metrics from various sources into Snowflake, enabling the creation of a centralized data lake. This integration supports complex analytics and machine learning workflows on cloud data.</p> </li> <li> <p><strong>Dynamic Business Intelligence Dashboards</strong>: Leverage the plugin to automatically generate tables from incoming metrics and feed them into BI tools. This allows businesses to create dynamic dashboards that visualize performance trends and operational insights without manual schema management.</p> </li> <li> <p><strong>Scalable IoT Analytics</strong>: Deploy the plugin to capture high-frequency data from IoT devices into Snowflake. This use case facilitates the aggregation and analysis of sensor data, enabling predictive maintenance and real-time monitoring at scale.</p> </li> <li> <p><strong>Historical Trend Analysis for Compliance</strong>: Use the plugin to log and archive detailed metric data in Snowflake, which can then be queried for long-term trend analysis and compliance reporting. This setup ensures that organizations can maintain a robust audit trail and perform forensic analysis if needed.</p> </li> </ol>

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Useful Links

Documentation

Telegraf Quickstart Training

Infrastructure Monitoring with Telegraf

Powerful Performance, Limitless Scale

Collect, organize, and act on massive volumes of high-velocity data. Any data is more valuable when you think of it as time series data. with InfluxDB, the #1 time series platform built to scale with Telegraf.

See Ways to Get Started

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